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swinv2-tiny-patch4-window8-256-DMAE-ex

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swinv2
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  1. README.md +37 -37
  2. model.safetensors +1 -1
  3. runs/Dec02_14-46-00_DESKTOP-SKBE9FB/events.out.tfevents.1733172362.DESKTOP-SKBE9FB.11608.0 +2 -2
README.md CHANGED
@@ -32,7 +32,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3498
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  - Accuracy: 0.4565
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  ## Model description
@@ -52,7 +52,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.005
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -67,41 +67,41 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 0.86 | 3 | 6.1826 | 0.1087 |
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- | No log | 2.0 | 7 | 1.7806 | 0.3261 |
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- | 4.802 | 2.86 | 10 | 2.2338 | 0.1087 |
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- | 4.802 | 4.0 | 14 | 1.4061 | 0.3261 |
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- | 4.802 | 4.86 | 17 | 1.3498 | 0.4565 |
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- | 2.3987 | 6.0 | 21 | 1.5674 | 0.1087 |
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- | 2.3987 | 6.86 | 24 | 1.3750 | 0.3261 |
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- | 2.3987 | 8.0 | 28 | 1.4331 | 0.4565 |
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- | 1.4401 | 8.86 | 31 | 1.2785 | 0.3261 |
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- | 1.4401 | 10.0 | 35 | 1.2276 | 0.4565 |
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- | 1.4401 | 10.86 | 38 | 1.2260 | 0.4565 |
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- | 1.2542 | 12.0 | 42 | 1.2225 | 0.4565 |
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- | 1.2542 | 12.86 | 45 | 1.2367 | 0.4565 |
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- | 1.2542 | 14.0 | 49 | 1.2584 | 0.4565 |
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- | 1.3069 | 14.86 | 52 | 1.2062 | 0.4565 |
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- | 1.3069 | 16.0 | 56 | 1.2094 | 0.4565 |
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- | 1.3069 | 16.86 | 59 | 1.2351 | 0.4565 |
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- | 1.2418 | 18.0 | 63 | 1.2273 | 0.4565 |
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- | 1.2418 | 18.86 | 66 | 1.2197 | 0.4565 |
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- | 1.2399 | 20.0 | 70 | 1.2339 | 0.4565 |
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- | 1.2399 | 20.86 | 73 | 1.2420 | 0.3261 |
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- | 1.2399 | 22.0 | 77 | 1.2304 | 0.4565 |
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- | 1.2262 | 22.86 | 80 | 1.2176 | 0.4565 |
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- | 1.2262 | 24.0 | 84 | 1.2134 | 0.4565 |
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- | 1.2262 | 24.86 | 87 | 1.2083 | 0.4565 |
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- | 1.1989 | 26.0 | 91 | 1.2147 | 0.4565 |
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- | 1.1989 | 26.86 | 94 | 1.2231 | 0.4565 |
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- | 1.1989 | 28.0 | 98 | 1.2131 | 0.4565 |
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- | 1.1991 | 28.86 | 101 | 1.2088 | 0.4565 |
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- | 1.1991 | 30.0 | 105 | 1.2073 | 0.4565 |
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- | 1.1991 | 30.86 | 108 | 1.2109 | 0.4565 |
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- | 1.2015 | 32.0 | 112 | 1.2093 | 0.4565 |
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- | 1.2015 | 32.86 | 115 | 1.2076 | 0.4565 |
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- | 1.2015 | 34.0 | 119 | 1.2067 | 0.4565 |
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- | 1.1997 | 34.29 | 120 | 1.2065 | 0.4565 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2072
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  - Accuracy: 0.4565
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  ## Model description
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.004
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.86 | 3 | 6.6832 | 0.1087 |
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+ | No log | 2.0 | 7 | 1.2148 | 0.4565 |
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+ | 4.4686 | 2.86 | 10 | 2.5061 | 0.3261 |
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+ | 4.4686 | 4.0 | 14 | 1.4142 | 0.4565 |
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+ | 4.4686 | 4.86 | 17 | 1.6118 | 0.4565 |
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+ | 1.7414 | 6.0 | 21 | 1.2484 | 0.4565 |
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+ | 1.7414 | 6.86 | 24 | 1.3690 | 0.3261 |
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+ | 1.7414 | 8.0 | 28 | 1.4065 | 0.4565 |
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+ | 1.3568 | 8.86 | 31 | 1.2682 | 0.3261 |
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+ | 1.3568 | 10.0 | 35 | 1.2140 | 0.4565 |
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+ | 1.3568 | 10.86 | 38 | 1.2591 | 0.4565 |
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+ | 1.2275 | 12.0 | 42 | 1.2519 | 0.4565 |
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+ | 1.2275 | 12.86 | 45 | 1.2184 | 0.4565 |
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+ | 1.2275 | 14.0 | 49 | 1.2592 | 0.4565 |
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+ | 1.3025 | 14.86 | 52 | 1.2246 | 0.4565 |
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+ | 1.3025 | 16.0 | 56 | 1.3046 | 0.4565 |
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+ | 1.3025 | 16.86 | 59 | 1.2177 | 0.4565 |
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+ | 1.2981 | 18.0 | 63 | 1.2339 | 0.4565 |
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+ | 1.2981 | 18.86 | 66 | 1.3139 | 0.4565 |
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+ | 1.2765 | 20.0 | 70 | 1.2116 | 0.4565 |
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+ | 1.2765 | 20.86 | 73 | 1.2284 | 0.3261 |
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+ | 1.2765 | 22.0 | 77 | 1.2246 | 0.4565 |
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+ | 1.2074 | 22.86 | 80 | 1.2631 | 0.4565 |
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+ | 1.2074 | 24.0 | 84 | 1.2092 | 0.4565 |
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+ | 1.2074 | 24.86 | 87 | 1.2147 | 0.4565 |
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+ | 1.2048 | 26.0 | 91 | 1.2121 | 0.4565 |
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+ | 1.2048 | 26.86 | 94 | 1.2156 | 0.4565 |
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+ | 1.2048 | 28.0 | 98 | 1.2249 | 0.4565 |
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+ | 1.2068 | 28.86 | 101 | 1.2159 | 0.4565 |
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+ | 1.2068 | 30.0 | 105 | 1.2108 | 0.4565 |
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+ | 1.2068 | 30.86 | 108 | 1.2116 | 0.4565 |
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+ | 1.1961 | 32.0 | 112 | 1.2078 | 0.4565 |
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+ | 1.1961 | 32.86 | 115 | 1.2070 | 0.4565 |
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+ | 1.1961 | 34.0 | 119 | 1.2072 | 0.4565 |
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+ | 1.1999 | 34.29 | 120 | 1.2072 | 0.4565 |
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  ### Framework versions
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